A refutational approach to geometry theorem proving

IF 4.6 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Artificial Intelligence Pub Date : 1988-12-01 DOI:10.1016/0004-3702(88)90050-1
Deepak Kapur
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引用次数: 0

Abstract

A refutational method for proving universally quantified formulae in algebraic geometry is proposed. A geometry statement to be proved is usually stated as a finite set of hypotheses implying a conclusion. A hypothesis is either a polynomial equation expressing a geometric relation or a polynomial inequation (the negation of a polynomial equation) expressing a subsidiary condition that rules out degenerate cases and perhaps some general cases. A conclusion is a polynomial equation expressing a geometry relation to be derived. Instead of showing that the conclusion directly follows from the hypothesis equations and inequations, the proof-by-contradiction technique is employed. It is checked whether the negation of the conclusion is inconsistent with the hypotheses. This can be done by converting the hypotheses and the negation of the conclusion into a finite set of polynomial equations and checking that they do not have a common solution. There exist many methods for this check, thus giving a complete decision procedure for such geometry statements. This approach has been recently employed to automatically prove a number of interesting theorems in plane Euclidean geometry. A Gröbner basis algorithm is used to check whether a finite set of polynomial equations does not have a solution. Two other formulations of geometry problems are also discussed and complete methods for solving them using the Gröbner basis computations are given.
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几何定理证明的一种反驳方法
提出了一种证明代数几何中普遍量化公式的反驳方法。一个待证明的几何命题通常被表述为包含一个结论的有限假设集。假设要么是表示几何关系的多项式方程,要么是表示排除退化情况和某些一般情况的辅助条件的多项式不等式(多项式方程的否定)。结论是表示待导出的几何关系的多项式方程。采用了反证法,而不是直接从假设方程和不等式中得出结论。检查结论的否定是否与假设不一致。这可以通过将假设和结论的否定转换成一组有限的多项式方程并检查它们没有公共解来完成。这种检验方法有很多种,从而给出了这种几何语句的完整判定过程。这种方法最近被用来自动证明平面欧几里得几何中的一些有趣的定理。一个Gröbner基算法被用来检查一个有限的多项式方程组是否没有解。本文还讨论了几何问题的另外两种表述,并给出了利用Gröbner基计算求解这些问题的完整方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Artificial Intelligence
Artificial Intelligence 工程技术-计算机:人工智能
CiteScore
11.20
自引率
1.40%
发文量
118
审稿时长
8 months
期刊介绍: The Journal of Artificial Intelligence (AIJ) welcomes papers covering a broad spectrum of AI topics, including cognition, automated reasoning, computer vision, machine learning, and more. Papers should demonstrate advancements in AI and propose innovative approaches to AI problems. Additionally, the journal accepts papers describing AI applications, focusing on how new methods enhance performance rather than reiterating conventional approaches. In addition to regular papers, AIJ also accepts Research Notes, Research Field Reviews, Position Papers, Book Reviews, and summary papers on AI challenges and competitions.
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